3 papers
cs.CV2025
Towards Railway Domain Adaptation for LiDAR-based 3D Detection: Road-to-Rail and Sim-to-Real via SynDRA-BBox
Xavier Diaz, Gianluca D'Amico, Raul Dominguez-Sanchez +3
In recent years, interest in automatic train operations has significantly increased. To enable advanced functionalities, robust vision-based algorithms are essential for perceiving…
cs.CV2025
A Data-Centric Approach to 3D Semantic Segmentation of Railway Scenes
Nicolas Münger, Max Peter Ronecker, Xavier Diaz +3
LiDAR-based semantic segmentation is critical for autonomous trains, requiring accurate predictions across varying distances. This paper introduces two targeted data augmentation m…
cs.RO2024
Deep Learning-Driven State Correction: A Hybrid Architecture for Radar-Based Dynamic Occupancy Grid Mapping
Max Peter Ronecker, Xavier Diaz, Michael Karner +1
This paper introduces a novel hybrid architecture that enhances radar-based Dynamic Occupancy Grid Mapping (DOGM) for autonomous vehicles, integrating deep learning for state-class…